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or the moment almost all the research on liquidity, other than that carried out by econophysicists such as Bouchaud, Potters, Mezard, Wyart, French, Farmer, and others, has been carried out against the traditional models of Debreu, Arrow, et al, and I am obliged to follow this in my review. 220 EFTA0
a Chli with regard to producing simulations of my models proposed in 2006. The exchange model proved difficult to construct. However, in March 2010 Maria and George produced the first Matlab model for me based on the GLV model in the second part of my 2006 note. Somewhat to my surprise, this produced
al and ecological scientists have the right mathematical tools for creating a radical and effective new economics, both specifically in the form of the Lotka-Volterra and maximum entropy production models, and more generally in their understanding of complex inter-related evolving systems. Ultimately this maths f
able, with assistance from George Vogiatzis and Maria Chli, to produce a GLV distribution of wealth fr
rom top to bottom. But this still results in a distribution with a large bias giving most of the wealth to a minority of individuals. Going back to the Lotka-Volterra and GLV models discussed in section 1.2, it is better to abandon the predator-prey model of foxes killing rabbits, and instead think in terms of a '
all outcomes are equally likely. The aim is 'to explain more by saying less', or at least start by saying less and see how far that takes us (c.f. Farmer et at (2005)). The principle that many market outcomes are determined more by the objective social structure than the particulars of individual rat
this is a chaotic model, not a stochastic one. There is no stochasticity in this model. All fluctuations in the model are created endogenously from the Lotka-Volterra like differential equations in the model. Figure 4.3.4 shows the detail of couple of cycles. Figure 4.3.4 here These are real live Minskian / Aus
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